This study examines the impact of parliamentary thresholds on the Indonesian political system through the lens of the Routine Policy Implementation Model and the Strategic Policy Implementation Model. The main objective is to evaluate the effectiveness of parliamentary thresholds in managing political fragmentation, assess their impact on stability and representation in the legislative system, and understand their implementation’s technical and strategic implications. Using a qualitative approach supported by interview studies and field observations, this research combines analysis of election data in the 2009, 2014, and 2019 elections with a qualitative assessment of policy changes and political dynamics. The Routine Policy Implementation Model focuses on the technical aspects of threshold implementation, including vote counting procedures and seat allocation efficiency. Meanwhile, the Strategic Policy Implementation Model examines the broader implications of these thresholds for political consolidation, government effectiveness, and the representation of minor parties. The results show that the parliamentary threshold has significantly reduced political fragmentation by consolidating the number of parties in Parliament, resulting in a legislative system that is cleaner and easier to administer. However, this consolidation has also marginalized small parties and limited political diversity. The novelty of this study lies in its comprehensive analysis of how parliamentary thresholds affect administrative efficiency and strategic political stability in Indonesia, compared to democratic countries in transition, such as Slovenia and Montenegro. In conclusion, although parliamentary thresholds have increased political stability and government effectiveness, they have also raised concerns about the reduced representation of small and regional parties. The study recommends maintaining balanced thresholds that ensure stability and diversity, implementing mechanisms to review thresholds periodically, and involving diverse stakeholders in adjusting policies to reflect evolving political dynamics. This approach will help balance the need for a stable legislative environment with broad representation.

This study uses the UTAUT2 (Unified theory of acceptance and use of technology) model as well as adding other factors such as Platform Usability, User Autonomy to determine the behavioral intention and behavior of online shoppers using e-commerce applications (ECAs) in Vietnam. Using the analysis results from structural equation modeling, it was shown that Social Influence, Use Proficiency, Hedonic Motivation, User Skill, Effort Expectancy positively affect Behavioral Intention. At the same time, Behavioral Intention is negatively affected by Performance Expectancy. Behavioral Intention and Facilitating Conditions are two factors that positively affect Use Behavior. Besides, User Autonomy negatively affects Use Behavior. The research results are an important basis for ECAs providers, managers and stakeholders to apply in assessing the behavioral intentions and behaviors of online shopping customers using ECAs in Vietnam to promote the use of ECAs in online shopping.

This financial modelling case study describes the development of the 3-statement financial model for a large-scale transportation infrastructure business dealing with truck (and some rail) modalities. The financial modelling challenges in this area, especially for large-scale transport infrastructure operators, lie in automatically linking the operating activity volumes with the investment volumes. The aim of the paper is to address these challenges: The proposed model has an innovative retirement/reinvestment schedule that automates the estimation of the investment needs for the Business based on the designated age-cohort matrix analysis and controlling for the maximum service ceiling for trucks as well as the possibility of truck retirements due to the reduced scope of tracking operations in the future. The investment schedule thus automated has a few calibrating parameters that help match it to the current stock of trucks/rolling stock in the fleet, making it to be a flexible tool in financial modelling for diverse transport infrastructure enterprises employing truck, bus and/or rail fleets for the carriage of bulk cargo quantifiable by weight (or fare-paying passengers) on a network of set, but modifiable, routes.

Digital transformation is a significant phenomenon that affects almost every business sector, particularly the telecommunications industry, which is closely intertwined with information technology. This study is grounded in McLuhan’s concept of technological determinism and Martin Heidegger’s philosophy of technology, which asserts that media and technology shape human thoughts and interactions, benefiting individuals, society, and culture alike. The primary objective of this research is to investigate the environmental factors that influence digital transformation and to assess its impact on the strategic renewal of a company. This research employs exploratory qualitative methods, collecting in-depth information through interviews with the respondents from Indonesia’s leading telecommunications operator who can provide comprehensive and contextual insights into digital transformation. The findings reveal specific environmental factors that drive digital transformation. The major identified components of strategic renewal include advancements in information technology, the role of human resources, and interactions with external parties, including customers and partners.

The creation of points where law, politics and education policies take intersection is a very complex and dynamic environment determined by philosophical shifts, economic problems, and social dynamics. This study dissects various complicated challenges facing the process of the framing of educational policies and their implementation which have become rampant due to the rapid political transformations. The researched evaluation is applied via both qualitative and quantitative methods, including juridical research, case and best practices studies and surveys, with the descriptive nature of the research as the main tool. The heart of the essay is three main themes - the contention between the rigidity of the academic standards and the holistic growth of students, its possible effects when students are too identified with a test-centric approach as their knowledge is sacrificed for their test scores, and the inclusion of rights and protections for underrepresented populations even when faced with a government’s resistance. Similarly, the research examines the perils of creating legislation too quickly, especially, because of unexpected side effects and interpretation conflicts. Findings show profound demographic differentials over districts which implies the designing and implementation of policies need to be modified accordingly. Unless a certain policy brings the best outcomes in the learning process, then nobody should choose it even if it means disrupting student well-being and decreasing their involvement. It is also emblematic of how cross-party cooperation and stakeholders’ understanding are important aspects of fairly dealing with complicated policy environments.

The cars industry has undergone significant technological advancements, with data analytics and artificial intelligence (AI) reshaping its operations. This study aims to examine the revolutionary influence of artificial intelligence and data analytics on the cars sector, particularly in terms of supporting sustainable business practices and enhancing profitability. Technology-organization-environment model and the triple bottom line technique were both used in this study to estimate the influence of technological factors, organizational factors, and environmental factors on social, environmental (planet), and economic. The data for this research was collected through a structured questionnaire containing closed questions. A total of 327 participants responded to the questionnaire from different professionals in the cars sector. The study was conducted in the cars industry, where the problem of the study revolved around addressing artificial intelligence in its various aspects and how it can affect sustainable business practices and firms’ profitability. The study highlights that the cars industry sector can be transformed significantly by using AI and data analytics within the TOE framework and with a focus on triple bottom line (TBL) outputs. However, in order to fully benefit from these advantages, new technologies need to be implemented while maintaining moral and legal standards and continuously developing them. This approach has the potential to guide the cars industry towards a future that is environmentally friendly, economically feasible, and socially responsible. The paper’s primary contribution is to assist professionals in the industry in strategically utilizing Artificial Intelligence and data analytics to advance and transform the industry.